Main
MA plot of H2Av normalization
RARA gene locus with CTCF Spike-in
Figure 2 can be viewed interactively on the USCS track.
H2av with DiffBind


Comparison of DiffBind output before and after applying the corrected size factors from our pipeline generated from Drosophila spike-in control. (A) Analysis of ER binding before and after treatment with fulvestrant demonstrates that DiffBind’s default normalisation strategy is more effective than the DESeq2 default, but demonstrates a bias between samples. (B) Applying the correct size factors from our DESeq2 pipeline reduces the bias in the analysis (Data: SLX-8047).
Normalisation factors are consistent over a wide range in number of control binding sites

Stability of CTCF derived normalisation coefficient. Stability of the CTCF derived normalisation coefficient was analysed by sub-sampling CTCF peaks before undertaking the calculation (between 1-100% of total sites) at random. This analysis was repeated 100 times to model the variability of the result.
Comparison of CTCF and H2Av normalisation methods

Supplementry
Comparison of simple normalisation methods
Method comparision

Comparison of ChIP-seq Pipelines.} (A)ChIPComp data was plot from the CountSet object, results show a high number of false positive up-regulated sites. (B) EdgeR normalisation is designed for the analysis of transcriptional data. In case of large-scale uni-direction changes in binding the assumption of normalisation fail give rise distribution that is artificially symmetric.(C) DeSEQ2 makes use of similar assumptions and results in a similar distortion of data. (D) DiffBind utilises normalisation to total library size, and performs significantly better than the other three methods but does not attempt to control for systematic bias in pull-down efficiency of the ChIP.
MA Plots of mouse ER normalization

MA plots showing the addition of Mm derived chromatin spike-in to the ChIP-seq analysis of MCF-7 before and after treatment with fulvestrant. (A) MA plot after scaling factor based normalisation shows same characteristic grouping of peaks off axis. (B) ER binding in Mm samples shows considerable increase in binding after treatment of the MCF-7 cell line with fulvestrant. (C) Attempting to fit a correction factor to the data results in a significant distortion.
Relative reads aligments in mouse samples
MA plots of CTCF Parallel-Factor ChIP

MA plots showing ER binding before and after treatment with fulvestrant including matched CTCF control.} (A) Reads corrected to total aligned reads showed the same off-centre peak density as observed with all that was not-normalised with an internal spike-in control. (B) Overlaying the MA plot combining the changes in chromatin binding of ER (black) and CTCF (grey). CTCF peaks overlay the off-centre peak density. (C) Utilising the CTCF binding events as a ground truth for 0-fold change, a linear fit to the log-fold change is generated (blue line). The fit is then also applied to the ER binding events.
ER and CTCF heatmaps



Clustering of samples before and after ER and CTCF peak extractions shows the effect of fulvestrant on ER peaks drive clustering of the raw data.} To confirm that the effects seen at the RARa locus were consistent across the genome, we compared the clustering of the CTCF and the ER peaks with respect to the treatment with fulvestrant. Initial clustering was weakly correlated with that of the treatment condition (A). Clustering specifically to CTCF derived peak data (B) resulted in a loss of grouping by treatment, while clustering specifically ER-derived peak data (C) led to a clearer separation by treatment.
Comparison of control regions


Comparison of the control regions used to normalise ER analysis before and after treatment. Dots highlighted in red are significant (FDR = 0.01). (A) H2Av occupancy of the Drosophila genome shows no significant changes before and after treatment. (B) The CTCF peaks used for normalisation show no significant change in the number reads before and after treatment.
Cross normalisation

Activation of ER in MCF7

Comparison of fold-change of ER binding before and after treatment with estradiol. MA plot of ER binding after normalisation to CTCF binding displays a significant increase in ER binding at 45 minutes after treatment with estradiol.

Comparison of log(Counts) for binding sites was under taken to confirm reproducibility. The data with the lowest correlation is shown and was seen between Replicate 1 and Replicate 3 in the control condition.
Comparision of ER binding from public datasets
Comparison ER binding from public datasets.Common peaks detected for ER Ross-Innes CS, et al. 2010; Welboren WJ, et al., 2009; Ceschin DG, et al. 2011 and our data (FDR = 0.01). Venn diagram was generated with ChIPSeqAnno. 
Changes in H4K12ac following E2 treatment

Comparison of fold-change of H4 acetylation (Lys12) before and after treatment with estradiol. MA plot of H4K12ac after normalisation to CTCF binding displays an increase at 2 hours after treatment with estradiol.

Comparison of log(Counts) for binding sites was under taken to confirm reproducibility. The data with the lowest correlation is shown and was seen between Replicate 2 and Repelicate 3 in the control condition.

H4k12ac occupancy profile before and after treatment with E2 shows a general increase around transcription start sites (TSS).
Activation of ER in MCF7

Comparison of fold-change of ER binding before and after treatment with estradiol. MA plot of ER binding after normalisation to CTCF binding displays a significant increase in ER binding at 45 minutes after treatment with estradiol.

Comparison of log(Counts) for binding sites was under taken to confirm reproducibility. The data with the lowest correlation is shown and was seen between Replicate 1 and Replicate 3 in the control condition.